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xxczaki
by xxczaki

Local History MCP Server

Access Cursor/VS Code Local History through the Model Context Protocol for AI-powered data recovery

CI Release MCP

Overview

This MCP server bridges the gap between AI assistants and editor Local History, enabling data recovery and enhanced context awareness. Unlike undo/redo, Local History captures file snapshots at save points, preserving work that would otherwise be lost.

Problem: Current AI assistants (Claude, Cursor AI, GitHub Copilot) cannot access Local History data despite having extensive diagnostic capabilities.

Solution: Simple MCP server providing direct access to Cursor/VS Code Local History for personal use.

Related MCP server: Pippa MCP Memory Manager

Installation

Install using your preferred package manager:

# npm npx local-history-mcp # pnpm pnpm dlx local-history-mcp # yarn yarn global add local-history-mcp # bun bunx local-history-mcp

Option 2: From Source

git clone https://github.com/xxczaki/local-history-mcp.git && cd local-history-mcp pnpm install pnpm build pnpm start

MCP Tools

Tool

Description

list_history_files

List all files with Local History

get_file_history

View complete history for a file

get_history_entry

Get specific history entry content

restore_from_history

Restore file to previous state (with backup)

search_history_content

Search across all history entries

get_history_stats

Overview statistics

Configuration

Cursor

You can install this MCP server in Cursor using the one-click install button:

Install MCP Server

Or manually configure by following the official Cursor MCP documentation.

Claude Code & Claude Desktop

For Claude Code (CLI), install directly:

claude mcp add local-history -- npx -y local-history-mcp

For Claude Desktop, see the official MCP documentation.

VS Code

See the official documentation.

Development

# Development mode pnpm dev # Run tests pnpm test # Linting and formatting pnpm lint # Launch MCP Inspector pnpm inspector

AI disclosure

This project contains code generated by Large Language Models (LLMs), under human supervision and proofreading.

License

MIT

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